About the role
AI summarisedWe are seeking a highly skilled Data Scientist with expertise in AI and Data Science to design, implement, and optimize advanced analytics and machine learning solutions. This role requires strong technical proficiency, business acumen, and innovative thinking to deliver actionable insights and drive data-driven decision-making. The position involves understanding business requirements, translating them into data-driven strategies, and developing solutions that improve operational efficiency and overall business performance.
FablessOnsiteData Science
Key Responsibilities
- Build and deploy AI/ML workflows, leveraging Large Language Models (LLMs) and AI agents for automation
- Develop and maintain scalable, reliable data pipelines using tools such as Python, Spark, and Kafka to ensure data accessibility and performance for machine learning applications
- Gather and interpret business requirements to design data-driven solutions that address key challenges and improve efficiency
- Collect, clean, and analyze large datasets (structured and unstructured) to identify trends, patterns, and actionable insights
- Develop predictive and prescriptive models to support decision-making and optimize business processes
- Create dashboards, reports, and visualizations using tools like Tableau or Power BI to communicate insights effectively to stakeholders
- Collaborate with cross-functional teams—including business units, data engineers, and software developers—to ensure alignment between analytics solutions and organizational goals
- Partner with cross-functional teams—including data engineers, software developers, and business stakeholders—to define requirements, integrate systems, and present findings in clear, actionable formats
Requirements
- Expertise in Python and the data/ai ecosystem libraries and frameworks
- Solid foundation in data architecture, statistics, machine learning, deep learning, and data science techniques
- Experience handling large scale data distributed data for deep analysis
- Working knowledge of LLMs, Agents and Agentic workflows
- Demonstrated capability to develop scalable data integrations following best practices for data quality, security, and governance in enterprise environments
- Hands-on experience with tools and platforms such as: Big Data Technologies: Apache Spark, Hive, Presto Cloud Platforms: AWS, Azure, GCP Databases: SQL, NoSQL, vector databases Visualization Tools: Tableau, Power BI
- Exceptional analytical and problem-solving skills with a focus on delivering production-grade solutions that drive measurable business impact
- Preferred 7+ years of hands-on experience in data science, machine learning, or advanced analytics in enterprise-scale environments
- Bachelor’s degree in Computer Science, Engineering, Statistics, Applied Mathematics, or a related quantitative field